A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19

Comprehensive characterization of human-virus protein-protein interactions reveals disease comorbidities and potential antiviral drugs

The protein-protein interactions (PPIs) between human and viruses play important roles in viral infection and host immune responses. Rapid accumulation of experimentally validated human-virus PPIs provides an unprecedented opportunity to investigate the regulatory pattern of viral infection. However, we are still lack of knowledge about the regulatory patterns of human-virus interactions. We collected 27,293 experimentally validated human-virus PPIs, covering 8 virus families, 140 viral proteins and 6059 human proteins. Functional enrichment analysis revealed that the viral interacting proteins were likely to be enriched in cell cycle and immune-related pathways. Moreover, we analysed the topological features of the viral interacting proteins and found that they were likely to locate in central regions of human PPI network. Based on network proximity analyses of diseases genes and human-virus interactions in the human interactome, we revealed the associations between complex diseases and viral infections. Network analysis also implicated potential antiviral drugs that were further validated by text mining. Finally, we presented the Human-Virus Protein-Protein Interaction database (HVPPI, http://bio-bigdata.hrbmu.edu.cn/HVPPI), that provides experimentally validated human-virus PPIs as well as seamlessly integrates online functional analysis tools. In summary, comprehensive understanding the regulatory pattern of human-virus interactome will provide novel insights into fundamental infectious mechanism discovery and new antiviral therapy development.

[Potentially useful drugs in the treatment of COVID-19 in Primary Care]

The consequences of the SARS-CoV-2 pandemic have exceeded any forecast made. Today we know that the level of severity of the infection in its initial stages will correspond to the evolution and the presence of sequelae in the future. There are no specific treatments that have shown sufficient evidence to allow their recommendation, especially in the mild-moderate stages of the disease. The anti-Covid vaccination is showing clear benefits, both in the prevention of the disease and in its evolution, with the consequent improvement in the numbers of those affected by the pandemic. The use of different drugs used in other indications has been proposed as possible beneficial treatments for COVID-19 that, if used, will be prescribed individually taking into account the characteristics and situation of the patient, the evolutionary phase of the disease as well as well as the limitations of the lack of evidence in its administration.

Modulation of Inflammatory Cytokine Production in Human Monocytes by cGMP and IRAK3

Interleukin-1 receptor-associated kinase-3 (IRAK3) is a critical checkpoint molecule of inflammatory responses in the innate immune system. The pseudokinase domain of IRAK3 contains a guanylate cyclase (GC) centre that generates small amounts of cyclic guanosine monophosphate (cGMP) associated with IRAK3 functions in inflammation. However, the mechanisms of IRAK3 actions are poorly understood. The effects of low cGMP levels on inflammation are unknown, therefore a dose–response effect of cGMP on inflammatory markers was assessed in THP-1 monocytes challenged with lipopolysaccharide (LPS). Sub-nanomolar concentrations of membrane permeable 8-Br-cGMP reduced LPS-induced NFκB activity, IL-6 and TNF-α cytokine levels. Pharmacologically upregulating cellular cGMP levels using a nitric oxide donor reduced cytokine secretion. Downregulating cellular cGMP using a soluble GC inhibitor increased cytokine levels. Knocking down IRAK3 in THP-1 cells revealed that unlike the wild type cells, 8-Br-cGMP did not suppress inflammatory responses. Complementation of IRAK3 knockdown cells with wild type IRAK3 suppressed cytokine production while complementation with an IRAK3 mutant at GC centre only partially restored this function. Together these findings indicate low levels of cGMP form a critical component in suppressing cytokine production and in mediating IRAK3 action, and this may be via a cGMP enriched nanodomain formed by IRAK3 itself.

Melatonin: highlighting its use as a potential treatment for SARS-CoV-2 infection

Numerous pharmaceutical drugs have been repurposed for use as treatments for COVID-19 disease. These drugs have not consistently demonstrated high efficacy in preventing or treating this serious condition and all have side effects to differing degrees. We encourage the continued consideration of the use of the antioxidant and anti-inflammatory agent, melatonin, as a countermeasure to a SARS-CoV-2 infection. More than 140 scientific publications have identified melatonin as a likely useful agent to treat this disease. Moreover, the publications cited provide the rationale for the use of melatonin as a prophylactic agent against this condition. Melatonin has pan-antiviral effects and it diminishes the severity of viral infections and reduces the death of animals infected with numerous different viruses, including three different coronaviruses. Network analyses, which compared drugs used to treat SARS-CoV-2 in humans, also predicted that melatonin would be the most effective agent for preventing/treating COVID-19. Finally, when seriously infected COVID-19 patients were treated with melatonin, either alone or in combination with other medications, these treatments reduced the severity of infection, lowered the death rate, and shortened the duration of hospitalization. Melatonin’s ability to arrest SARS-CoV-2 infections may reduce health care exhaustion by limiting the need for hospitalization. Importantly, melatonin has a high safety profile over a wide range of doses and lacks significant toxicity. Some molecular processes by which melatonin resists a SARS-CoV-2 infection are summarized. The authors believe that all available, potentially beneficial drugs, including melatonin, that lack toxicity should be used in pandemics such as that caused by SARS-CoV-2.

A Workflow of Integrated Resources to Catalyze Network Pharmacology Driven COVID-19 Research

In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, host-pathogen, and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy. Here, we describe a workflow we designed for a semiautomated integration of rapidly emerging data sets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 63 278 host-host protein, and 1221 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is made publicly accessible via a web interface and via API calls based on the Bolt protocol. Details for accessing the database are provided on a landing page (https://neo4covid19.ncats.io/). We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19.

Phytomelatonin: a potential phytotherapeutic intervention on COVID-19-exposed individuals

Phytomelatonin is a pleiotropic molecule that originated in higher plants with many diverse actions and is primarily an antioxidant. The recent identification and advancement of phytomelatonin unraveled the potential of this modulatory molecule being considered a new plant hormone, suggesting its relevance in treating respiratory infections, including COVID-19. Besides, this molecule is also involved in multiple hormonal, physiological, and biological processes at different levels of cell organization and has been marked for its ability to cross the blood-brain barrier and prominent antioxidant effects, reducing mitochondrial electron leakage, up-regulating antioxidant enzymes, acting as a free radical scavenger, and interfering with pro-inflammatory signaling pathways as seen in mood swings, body temperature, sleep, cancer, cardiac rhythms, and immunological regulation modulators. However, due to its diversity, availability, affordability, convenience, and high safety profile, phytomelatonin has also been suggested as a natural adjuvant. This review discussed the origin, content in various plant species, processes of extraction, and detection and therapeutic potentials of phytomelatonin in treating COVID-19-exposed individuals.

Melatonin, Zinc, and Vitamin C: Potential Adjuvant Treatment for COVID-19 Patients

The use of nutraceutical approaches may regulate the immune system, performing a potential strategy to contain the worst outcomes of COVID-19. We reviewed the current evidence surrounding nutritional/nutraceutical approaches for the therapy in patients with COVID-19. We searched the PubMed database to report randomized controlled trials (RCTs) and observational research that used melatonin, zinc, or vitamin C supplementation as an intervention for COVID-19 treatment. To date, we found only three concluded studies that assessed zinc supplementation and melatonin therapy in patients with COVID-19, but with inconclusive data, relatively small sample size, and early termination of the trial. On the other hand, vitamin C therapy appears to reduce hyperinflammation and improve the oxygen support status of patients with COVID-19. However, a large part of this research involves pilot trials, and there are still conflicting data regarding mortality rate, mechanical ventilation, and duration of symptoms of patients with COVID-19. Melatonin, zinc, and vitamin C supplementation should be investigated further on the nutritional status-immune response, and data from ongoing trials are needed to understand these molecules as a therapy strategy in patients COVID-19.

Looking at COVID-19 from a Systems Biology Perspective

The sudden outbreak and worldwide spread of the SARS-CoV-2 pandemic pushed the scientific community to find fast solutions to cope with the health emergency. COVID-19 complexity, in terms of clinical outcomes, severity, and response to therapy suggested the use of multifactorial strategies, characteristic of the network medicine, to approach the study of the pathobiology. Proteomics and interactomics especially allow to generate datasets that, reduced and represented in the forms of networks, can be analyzed with the tools of systems biology to unveil specific pathways central to virus-human host interaction. Moreover, artificial intelligence tools can be implemented for the identification of druggable targets and drug repurposing. In this review article, we provide an overview of the results obtained so far, from a systems biology perspective, in the understanding of COVID-19 pathobiology and virus-host interactions, and in the development of disease classifiers and tools for drug repurposing.

Integrative COVID-19 biological network inference with probabilistic core decomposition

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for millions of deaths around the world. To help contribute to the understanding of crucial knowledge and to further generate new hypotheses relevant to SARS-CoV-2 and human protein interactions, we make use of the information abundant Biomine probabilistic database and extend the experimentally identified SARS-CoV-2-human protein-protein interaction (PPI) network in silico. We generate an extended network by integrating information from the Biomine database, the PPI network and other experimentally validated results. To generate novel hypotheses, we focus on the high-connectivity sub-communities that overlap most with the integrated experimentally validated results in the extended network. Therefore, we propose a new data analysis pipeline that can efficiently compute core decomposition on the extended network and identify dense subgraphs. We then evaluate the identified dense subgraph and the generated hypotheses in three contexts: literature validation for uncovered virus targeting genes and proteins, gene function enrichment analysis on subgraphs and literature support on drug repurposing for identified tissues and diseases related to COVID-19. The major types of the generated hypotheses are proteins with their encoding genes and we rank them by sorting their connections to the integrated experimentally validated nodes. In addition, we compile a comprehensive list of novel genes, and proteins potentially related to COVID-19, as well as novel diseases which might be comorbidities. Together with the generated hypotheses, our results provide novel knowledge relevant to COVID-19 for further validation.

Potential and Possible Therapeutic Effects of Melatonin on SARS-CoV-2 Infection

The absence of effective drugs for COVID-19 prevention and treatment requires the search for new candidates among approved medicines. Fundamental studies and clinical observations allow us to approach an understanding of the mechanisms of damage and protection from exposure to SARS-CoV-2, to identify possible points of application for pharmacological interventions. In this review we presented studies on the anti-inflammatory, antioxidant, and immunotropic properties of melatonin. We have attempted to present scientifically proven mechanisms of action for the potential therapeutic use of melatonin during SARS-CoV-2 infection. A wide range of pharmacological properties allows its inclusion as an effective addition to the methods of prevention and treatment of COVID-19.

Computational approaches for drug repositioning and repurposing to combat SARS-CoV-2 infection

Drug repositioning (also referred to as drug repurposing) is the method of exploring novel therapeutic indications for Food and Drug Administration-approved clinically implemented drugs. The unique strategy of drug repositioning is used to boost the drug development process since drug discovery is an expensive, arduous, cumbersome, and high-risk procedure. Recently, several pharmaceutical firms have used the drug repositioning technique in their drug discovery and development programs to develop new medications based on the identification of new therapeutic targets. This technique is extremely effective, saves time, is comparatively economical, and has a low chance of failure. Developing appropriate treatment measures to inhibit the spread of Coronavirus disease-2019 (COVID-19) is currently a top priority. As a result, several studies were conducted to build novel therapeutic molecules using diverse strategies of drug repurposing to discover drug candidates against COVID-19 infection that can act as substantial inhibitors against virus particles. By implementing virtual screening of drug libraries, it is possible to identify potential drugs through drug repurposing. A molecular docking approach and calculation of binding free energy are used to estimate binding affinity and drug–receptor interactions. Drug-repurposing methodologies can be divided into three categories: target-oriented, drug-oriented, and disease-oriented, based on the gathered data about the various physicochemical, pharmacokinetic and pharmacological features of a drug candidate. Using computational methods such as homology modeling and molecular similarity, this methodology aids in determining the binding interaction of drug molecules with the target protein of the virus. In this book chapter, we explore a typical set of currently utilized computational techniques for identifying repurposable drug molecules for COVID-19, as well as their supporting databases. We also assess promising drugs anticipated by computational approaches to drugs currently being evaluated in clinical trials. Moreover, we also examine the takeaways from the evaluated research efforts, such as how to competently combine bioinformatics tools with experimental work and suggest a fully integrated drug-repurposing approach to combat the deadly COVID-19 infection.

A fuzzy logic-based computational method for the repurposing of drugs against COVID-19

Introduction: COVID-19 has spread out all around the world and seriously interrupted human activities. Being a newfound disease, not only many aspects of the disease are unknown, but also there is not an effective medication to cure the disease. Besides, designing a drug is a time-consuming process and needs large investment. Hence, drug repurposing techniques, employed to discover the hidden benefits of the existing drugs, maybe a useful option for treating COVID-19. Methods: The present study exploits the drug repositioning concepts and introduces some candidate drugs which may be effective in controlling COVID-19. The suggested method consists of three main steps. First, the required data such as the amino acid sequences of targets and drug-target interactions are extracted from the public databases. Second, the similarity score between the targets (protein/enzymes) and genome of SARS-COV-2 is computed using the proposed fuzzy logic-based method. Since the classical approaches yield outcomes which may not be useful for the real-world applications, the fuzzy technique can address the issue. Third, after ranking targets based on the obtained scores, the usefulness of drugs affecting them is examined for managing COVID-19. Results: The results indicate that antiviral medicines, designed for curing hepatitis C, may also cure COVID-19. According to the findings, ribavirin, simeprevir, danoprevir, and XTL-6865 may be helpful in controlling the disease. Conclusion: It can be concluded that the similarity-based drug repurposing techniques may be the most suitable option for managing emerging diseases such as COVID-19 and can be applied to a wide range of data. Also, fuzzy logic-based scoring methods can produce outcomes which are more consistent with the real-world biological applications than others.

Role of mast cells in the pathogenesis of severe lung damage in COVID-19 patients

BACKGROUND

There is still insufficient knowledge with regard to the potential involvement of mast cells (MCs) and their mediators in the pathology of coronavirus disease-2019 (COVID-19). Therefore, our study aimed to investigate the role of MCs, their activation and protease profiles in the pathogenesis of early and late lung damage in COVID-19 patients.

METHODS

Formalin-fixed and paraffin embedded lung specimens from 30 patients who died from COVID-19 and 9 controls were used for histological detection of MCs and their proteases (tryptase, chymase) followed by morphometric quantification.

RESULTS

Our results demonstrated increased numbers of MCs at early stage and further augmentation of MCs number during the late stage of alveolar damage in COVID-19 patients, as compared to the control group. Importantly, the percentage of degranulated (activated) MCs was higher during both stages of alveolar lesions in comparison to the controls. While there was no prominent alteration in the profile of tryptase-positive MCs, our data revealed a significant elevation in the number of chymase-positive MCs in the lungs of COVID-19 patients, compared to the controls.

CONCLUSIONS

MCs are characterized by dysregulated accumulation and increased activation in the lungs of patients suffering from COVID-19. However, future profound studies are needed for precise analysis of the role of these immune cells in the context of novel coronavirus disease.

Post-COVID-19 Depressive Symptoms: Epidemiology, Pathophysiology, and Pharmacological Treatment

The Coronavirus Disease 2019 (COVID-19) pandemic is still spreading worldwide over 2 years since its outbreak. The psychopathological implications in COVID-19 survivors such as depression, anxiety, and cognitive impairments are now recognized as primary symptoms of the "post-acute COVID-19 syndrome." Depressive psychopathology was reported in around 35% of patients at short, medium, and long-term follow-up after the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection. Post-COVID-19 depressive symptoms are known to increase fatigue and affect neurocognitive functioning, sleep, quality of life, and global functioning in COVID-19 survivors. The psychopathological mechanisms underlying post-COVID-19 depressive symptoms are mainly related to the inflammation triggered by the peripheral immune-inflammatory response to the viral infection and to the persistent psychological burden during and after infection. The large number of SARS-CoV-2-infected patients and the high prevalence of post-COVID-19 depressive symptoms may significantly increase the pool of people suffering from depressive disorders. Therefore, it is essential to screen, diagnose, treat, and monitor COVID-19 survivors' psychopathology to counteract the depression disease burden and related years of life lived with disability. This paper reviews the current literature in order to synthesize the available evidence regarding epidemiology, clinical features, neurobiological underpinning, and pharmacological treatment of post-COVID-19 depressive symptoms.

Therapeutic potential of melatonin and melatonergic drugs on K18-hACE2 mice infected with SARS-CoV-2

As the COVID-19 pandemic grows, several therapeutic candidates are being tested or undergoing clinical trials. Although prophylactic vaccination against SARS-CoV-2 infection has been shown to be effective, no definitive treatment exists to date in the event of infection. The rapid spread of infection by SARS-CoV-2 and its variants fully warrants the continued evaluation of drug treatments for COVID-19, especially in the context of repurposing of already available and safe drugs. Here, we explored the therapeutic potential of melatonin and melatonergic compounds in attenuating COVID-19 pathogenesis in mice expressing human ACE2 receptor (K18-hACE2), strongly susceptible to SARS-CoV-2 infection. Daily administration of melatonin, agomelatine, or ramelteon delays the occurrence of severe clinical outcome with improvement of survival, especially with high melatonin dose. Although no changes in most lung inflammatory cytokines are observed, treatment with melatonergic compounds limits the exacerbated local lung production of type I and type III interferons, which is likely associated with the observed improved symptoms in treated mice. The promising results from this preclinical study should encourage studies examining the benefits of repurposing melatonergic drugs to treat COVID-19 and related diseases in humans.

Embracing the Complexity of Primary Health Care: System-Based Tools and Strategies for Researching the Case Management Process

The provision of health care is frequently a complex process, and favourable clinical outcomes are dependent on the effective management of this complexity. Contemporary medicine and health care practices that are biomedically aligned have been informed by a reductionist paradigm, potentially creating a misalignment between health care and the human organism as a complex adaptive system. Complexity science is increasingly gaining momentum within the academic literature and is being employed across a wide range of scientific disciplines, although this is less evident in medicine. Limited evidence was found within the literature of a complexity science framework being used to explore and inform individual health care practices; in this paper, this gap will be explored through consideration of the use of strategies and tools (specifically mind maps, computer-generated network mappings, exploratory data analysis, and computer-derived network analysis) which are congruent with a complexity science framework. This information may be useful to researchers investigating health care provision and to clinicians wishing to incorporate a complexity sensibility within their practice.

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Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

Background

The recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.

Methods

RNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.

Results

Based on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19's main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis.

Conclusion

This study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.

Micronutrients for potential therapeutic use against COVID-19; a review

SARS CoV-2 has caused a pandemic that has challenged both clinicians and researchers in finding an effective treatment option. Currently there only exists a two series vaccine that has a high efficacy in preventing infection. There is no standard effective treatment against SARS CoV-2 however several nutraceuticals such as melatonin, zinc, selenium, vitamin C and vitamin D are being proposed as prevention and treatment options.

Multiomics integration-based molecular characterizations of COVID-19

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly became a global health challenge, leading to unprecedented social and economic consequences. The mechanisms behind the pathogenesis of SARS-CoV-2 are both unique and complex. Omics-scale studies are emerging rapidly and offer a tremendous potential to unravel the puzzle of SARS-CoV-2 pathobiology, as well as moving forward with diagnostics, potential drug targets, risk stratification, therapeutic responses, vaccine development and therapeutic innovation. This review summarizes various aspects of understanding multiomics integration-based molecular characterizations of COVID-19, which to date include the integration of transcriptomics, proteomics, genomics, lipidomics, immunomics and metabolomics to explore virus targets and developing suitable therapeutic solutions through systems biology tools. Furthermore, this review also covers an abridgment of omics investigations related to disease pathogenesis and virulence, the role of host genetic variation and a broad array of immune and inflammatory phenotypes contributing to understanding COVID-19 traits. Insights into this review, which combines existing strategies and multiomics integration profiling, may help further advance our knowledge of COVID-19.

Stress Decreases Host Viral Resistance and Increases Covid Susceptibility in Embryonic Stem Cells

Stress-induced changes in viral receptor and susceptibility gene expression were measured in embryonic stem cells (ESC) and differentiated progeny. Rex1 promoter-Red Fluorescence Protein reporter ESC were tested by RNAseq after 72hr exposures to control stress hyperosmotic sorbitol under stemness culture (NS) to quantify stress-forced differentiation (SFD) transcriptomic programs. Control ESC cultured with stemness factor removal produced normal differentiation (ND). Bulk RNAseq transcriptomic analysis showed significant upregulation of two genes involved in Covid-19 cell uptake, Vimentin (VIM) and Transmembrane Serine Protease 2 (TMPRSS2). SFD increased the hepatitis A virus receptor (Havcr1) and the transplacental Herpes simplex 1 (HSV1) virus receptor (Pvrl1) compared with ESC undergoing ND. Several other coronavirus receptors, Glutamyl Aminopeptidase (ENPEP) and Dipeptidyl Peptidase 4 (DPP4) were upregulated significantly in SFD>ND. Although stressed ESC are more susceptible to infection due to increased expression of viral receptors and decreased resistance, the necessary Covid-19 receptor, angiotensin converting enzyme (ACE)2, was not expressed in our experiments. TMPRSS2, ENPEP, and DPP4 mediate Coronavirus uptake, but are also markers of extra-embryonic endoderm (XEN), which arise from ESC undergoing ND or SFD. Mouse and human ESCs differentiated to XEN increase TMPRSS2 and other Covid-19 uptake-mediating gene expression, but only some lines express ACE2. Covid-19 susceptibility appears to be genotype-specific and not ubiquitous. Of the 30 gene ontology (GO) groups for viral susceptibility, 15 underwent significant stress-forced changes. Of these, 4 GO groups mediated negative viral regulation and most genes in these increase in ND and decrease with SFD, thus suggesting that stress increases ESC viral susceptibility. Taken together, the data suggest that a control hyperosmotic stress can increase Covid-19 susceptibility and decrease viral host resistance in mouse ESC. However, this limited pilot study should be followed with studies in human ESC, tests of environmental, hormonal, and pharmaceutical stressors and direct tests for infection of stressed, cultured ESC and embryos by Covid-19.

Drug repurposing for COVID-19: Approaches, challenges and promising candidates

Traditional drug development and discovery has not kept pace with threats from emerging and re-emerging diseases such as Ebola virus, MERS-CoV and more recently, SARS-CoV-2. Among other reasons, the exorbitant costs, high attrition rate and extensive periods of time from research to market approval are the primary contributing factors to the lag in recent traditional drug developmental activities. Due to these reasons, drug developers are starting to consider drug repurposing (or repositioning) as a viable alternative to the more traditional drug development process. Drug repurposing aims to find alternative uses of an approved or investigational drug outside of its original indication. The key advantages of this approach are that there is less developmental risk, and it is less time-consuming since the safety and pharmacological profile of the repurposed drug is already established. To that end, various approaches to drug repurposing are employed. Computational approaches make use of machine learning and algorithms to model disease and drug interaction, while experimental approaches involve a more traditional wet-lab experiments. This review would discuss in detail various ongoing drug repurposing strategies and approaches to combat the current COVID-19 pandemic, along with the advantages and the potential challenges.

Advances in the computational landscape for repurposed drugs against COVID-19

The COVID-19 pandemic has caused millions of deaths and massive societal distress worldwide. Therapeutic solutions are urgently needed, but de novo drug development remains a lengthy process. One promising alternative is computational drug repurposing, which enables the prioritization of existing compounds through fast in silico analyses. Recent efforts based on molecular docking, machine learning, and network analysis have produced actionable predictions. Some predicted drugs, targeting viral proteins and pathological host pathways are undergoing clinical trials. Here, we review this work, highlight drugs with high predicted efficacy and classify their mechanisms of action. We discuss the strengths and limitations of the published methodologies and outline possible future directions. Finally, we curate a list of COVID-19 data portals and other repositories that could be used to accelerate future research.

Poking COVID-19: Insights on Genomic Constraints among Immune-Related Genes between Qatari and Italian Populations

Host genomic information, specifically genomic variations, may characterize susceptibility to disease and identify people with a higher risk of harm, leading to better targeting of care and vaccination. Italy was the epicentre for the spread of COVID-19 in Europe, the first country to go into a national lockdown and has one of the highest COVID-19 associated mortality rates. Qatar, on the other hand has a very low mortality rate. In this study, we compared whole-genome sequencing data of 14398 adults and Qatari-national to 925 Italian individuals. We also included in the comparison whole-exome sequence data from 189 Italian laboratory-confirmed COVID-19 cases. We focused our study on a curated list of 3619 candidate genes involved in innate immunity and host-pathogen interaction. Two population-gene metric scores, the Delta Singleton-Cohort variant score (DSC) and Sum Singleton-Cohort variant score (SSC), were applied to estimate the presence of selective constraints in the Qatari population and in the Italian cohorts. Results based on DSC and SSC metrics demonstrated a different selective pressure on three genes (MUC5AC, ABCA7, FLNA) between Qatari and Italian populations. This study highlighted the genetic differences between Qatari and Italian populations and identified a subset of genes involved in innate immunity and host-pathogen interaction.

Synergistic Effects of Natural Compounds Toward Inhibition of SARS-CoV-2 3CL Protease

The biggest challenge in medical management and control of the COVID-19 pandemic is the nonavailability of the treatment molecules. While vaccines and other biotherapeutic products for managing COVID-19 have reached the market, a small-molecule cure is yet to be developed. This is relevant because the cost of production, storage, and ease of distribution of a small-molecule drug are significantly more favorable than those of biologics. In this paper, we present a multicompound approach, where two drug molecules are administered concurrently to offer an effective therapy for COVID-19. The co-action of the two compounds, each derived from natural origins, has been demonstrated against the 3CL protease, already recognized as a potential drug target for inhibiting SARS-CoV-2. The pair of compounds pursued in this study are flavonoid and naphthalene scaffold. Individually, they offer ∼30 to 35% inhibition at 10 μM. Comprehensive docking and molecular dynamics simulations elucidate that these compounds exhibit excellent binding in the process, which however quickly deteriorates, and the ligand is separated from the binding site. This suggests that while the ligands initially bind with the protease, they are unable to maintain it for an extended period. However, the simulation showed that a simultaneous docked complex of both the compounds together with the protein boosts the stronger binding for a sufficient time. The enzyme assay exhibited 97 and 85% inhibition activity when both compounds were used together at 100 and 50 μM, respectively. Later, a multiconcentration assay was used to determine the coinhibitory activity, and it was observed that the compounds have ∼20 to 30% inhibition activity even at lower concentrations of 0.5 and 1 μM. Surface plasmon resonance was used to measure the binding of the compounds, and when used together, the compounds had a 10-fold greater binding affinity. Thus, the results demonstrate a synergistic mechanism between the two compounds that enhances the inhibition activity against SARS-CoV-2 3CL protease.

Pharmacological and philosophical considerations for the around-the-clock use of scheduled melatonin to promote sedation and reduce aggression in individuals with serious mental illness: a case report

Melatonin, the endogenous hormone that helps maintain circadian rhythm, has been used exogenously for both primary and secondary sleep disorders. While the effects of melatonin given prior to planned sleep and to restore normal circadian sleep phases have been well studied, there is little information on the use of melatonin as a pharmacotherapeutic intervention for around-the-clock sedation to prevent agitation and aggressive patient behaviors. This is the first case report to our knowledge of melatonin used throughout the day, as a scheduled dose for prolonged treatment duration, to reduce aggression in a patient with severe mental illness.

Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets

Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism targeting as a promising antiviral strategy.

Deficient synthesis of melatonin in COVID-19 can impair the resistance of coronavirus patients to mucormycosis

In addition to uncontrolled diabetes and the excess use of corticosteroids, it is believed that other factors may be responsible for the recent spurt of COVID-19 associated mucormycosis (CAM). In the present paper it is argued that COVID-19 increases the susceptibility of the patients to mucormycosis by augmenting the virulence factors of the mucor species, where deficient synthesis of melatonin plays a key role. Melatonin is synthesized from tryptophan via the serotonin pathway and melatonin deficiency in COVID-19 arises from the faulty absorption of tryptophan from the food because SARS-CoV-2 downregulates angiotensin-converting enzyme-2, the chaperone of the transporter of tryptophan. The enhanced fungal virulence in COVID-19 can be mitigated by correcting the melatonin deficiency as melatonin can prevent iron acquisition of the mucor species and inhibit their morphological transition from the yeast to the virulent hyphal form, given the fact that melatonin is an iron chelator, calmodulin blocker and inhibitor of myeloperoxidase as well as inhibitor of ferroptosis and pyroptosis. Also, by lowering the expression of glucose-regulated protein 78 and by inhibiting the suppression of T-cell immunity, melatonin can further increase the resistance of the patients to mucormycosis. Accordingly, clinical trials should be carried out on tryptophan supplementation, administration of selective serotonin reuptake inhibitors (to increase serotonin, the precursor of melatonin), and exogenous melatonin to find out how they perform in eliminating or reducing the propensity of the coronavirus patients to CAM.

Mechanism of Phosgene-Induced Acute Lung Injury and Treatment Strategy

Phosgene (COCl₂) was once used as a classic suffocation poison and currently plays an essential role in industrial production. Due to its high toxicity, the problem of poisoning caused by leakage during production, storage, and use cannot be ignored. Phosgene mainly acts on the lungs, causing long-lasting respiratory depression, refractory pulmonary edema, and other related lung injuries, which may cause acute respiratory distress syndrome or even death in severe cases. Due to the high mortality, poor prognosis, and frequent sequelae, targeted therapies for phosgene exposure are needed. However, there is currently no specific antidote for phosgene poisoning. This paper reviews the literature on the mechanism and treatment strategies to explore new ideas for the treatment of phosgene poisoning.

Development of a Multi-Target Strategy for the Treatment of Vitiligo via Machine Learning and Network Analysis Methods

Vitiligo is a complex disorder characterized by the loss of pigment in the skin. The current therapeutic strategies are limited. The identification of novel drug targets and candidates is highly challenging for vitiligo. Here we proposed a systematic framework to discover potential therapeutic targets, and further explore the underlying mechanism of kaempferide, one of major ingredients from Vernonia anthelmintica (L.) willd, for vitiligo. By collecting transcriptome and protein-protein interactome data, the combination of random forest (RF) and greedy articulation points removal (GAPR) methods was used to discover potential therapeutic targets for vitiligo. The results showed that the RF model performed well with AUC (area under the receiver operating characteristic curve) = 0.926, and led to prioritization of 722 important transcriptomic features. Then, network analysis revealed that 44 articulation proteins in vitiligo network were considered as potential therapeutic targets by the GAPR method. Finally, through integrating the above results and proteomic profiling of kaempferide, the multi-target strategy for vitiligo was dissected, including 1) the suppression of the p38 MAPK signaling pathway by inhibiting CDK1 and PBK, and 2) the modulation of cellular redox homeostasis, especially the TXN and GSH antioxidant systems, for the purpose of melanogenesis. Meanwhile, this strategy may offer a novel perspective to discover drug candidates for vitiligo. Thus, the framework would be a useful tool to discover potential therapeutic strategies and drug candidates for complex diseases.

Exploring Drugs and Vaccines Associated with Altered Risks and Severity of COVID-19: A UK Biobank Cohort Study of All ATC Level-4 Drug Categories Reveals Repositioning Opportunities

Effective therapies for COVID-19 are still lacking, and drug repositioning is a promising approach to address this problem. Here, we adopted a medical informatics approach to repositioning. We leveraged a large prospective cohort, the UK-Biobank (UKBB, N ~ 397,000), and studied associations of prior use of all level-4 ATC drug categories (N = 819, including vaccines) with COVID-19 diagnosis and severity. Effects of drugs on the risk of infection, disease severity, and mortality were investigated separately. Logistic regression was conducted, controlling for main confounders. We observed strong and highly consistent protective associations with statins. Many top-listed protective drugs were also cardiovascular medications, such as angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARB), calcium channel blocker (CCB), and beta-blockers. Some other drugs showing protective associations included biguanides (metformin), estrogens, thyroid hormones, proton pump inhibitors, and testosterone-5-alpha reductase inhibitors, among others. We also observed protective associations by influenza, pneumococcal, and several other vaccines. Subgroup and interaction analyses were also conducted, which revealed differences in protective effects in various subgroups. For example, protective effects of flu/pneumococcal vaccines were weaker in obese individuals, while protection by statins was stronger in cardiovascular patients. To conclude, our analysis revealed many drug repositioning candidates, for example several cardiovascular medications. Further studies are required for validation.

Integrative resource for network-based investigation of COVID-19 combinatorial drug repositioning and mechanism of action

An effective monotherapy to target the complex and multifactorial pathology of SARS-CoV-2 infection poses a challenge to drug repositioning, which can be improved by combination therapy. We developed an online network pharmacology-based drug repositioning platform, COVID-CDR (http://vafaeelab.com/COVID19repositioning.html), that enables a visual and quantitative investigation of the interplay between the primary drug targets and the SARS-CoV-2-host interactome in the human protein-protein interaction network. COVID-CDR prioritizes drug combinations with potential to act synergistically through different, yet potentially complementary, pathways. It provides the options for understanding multi-evidence drug-pair similarity scores along with several other relevant information on individual drugs or drug pairs. Overall, COVID-CDR is a first-of-its-kind online platform that provides a systematic approach for pre-clinical in silico investigation of combination therapies for treating COVID-19 at the fingertips of the clinicians and researchers.

Host metabolic reprogramming in response to SARS-CoV-2 infection: A systems biology approach

Understanding the pathogenesis of SARS-CoV-2 is essential for developing effective treatment strategies. Viruses hijack the host metabolism to redirect the resources for their replication and survival. The influence of SARS-CoV-2 on host metabolism is yet to be fully understood. In this study, we analyzed the transcriptomic data obtained from different human respiratory cell lines and patient samples (nasopharyngeal swab, peripheral blood mononuclear cells, lung biopsy, bronchoalveolar lavage fluid) to understand metabolic alterations in response to SARS-CoV-2 infection. We explored the expression pattern of metabolic genes in the comprehensive genome-scale network model of human metabolism, Recon3D, to extract key metabolic genes, pathways, and reporter metabolites under each SARS-CoV-2-infected condition. A SARS-CoV-2 core metabolic interactome was constructed for network-based drug repurposing. Our analysis revealed the host-dependent dysregulation of glycolysis, mitochondrial metabolism, amino acid metabolism, nucleotide metabolism, glutathione metabolism, polyamine synthesis, and lipid metabolism. We observed different pro- and antiviral metabolic changes and generated hypotheses on how the host metabolism can be targeted for reducing viral titers and immunomodulation. These findings warrant further exploration with more samples and in vitro studies to test predictions.

Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets

Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism-targeting as a promising antiviral strategy.

An update on novel approaches for diagnosis and treatment of SARS-CoV-2 infection

The ongoing pandemic of coronavirus disease 2019 (COVID-19) has made a serious public health and economic crisis worldwide which united global efforts to develop rapid, precise, and cost-efficient diagnostics, vaccines, and therapeutics. Numerous multi-disciplinary studies and techniques have been designed to investigate and develop various approaches to help frontline health workers, policymakers, and populations to overcome the disease. While these techniques have been reviewed within individual disciplines, it is now timely to provide a cross-disciplinary overview of novel diagnostic and therapeutic approaches summarizing complementary efforts across multiple fields of research and technology. Accordingly, we reviewed and summarized various advanced novel approaches used for diagnosis and treatment of COVID-19 to help researchers across diverse disciplines on their prioritization of resources for research and development and to give them better a picture of the latest techniques. These include artificial intelligence, nano-based, CRISPR-based, and mass spectrometry technologies as well as neutralizing factors and traditional medicines. We also reviewed new approaches for vaccine development and developed a dashboard to provide frequent updates on the current and future approved vaccines.

The Circadian Clock, the Brain, and COVID-19: The Cases of Olfaction and the Timing of Sleep

Daily rhythms of behavior and neurophysiology are integral to the circadian clocks of all animals. Examples of circadian clock regulation in the human brain include daily rhythms in sleep-wake, cognitive function, olfactory sensitivity, and risk for ischemic stroke, all of which overlap with symptoms displayed by many COVID-19 patients. Motivated by the relatively unexplored, yet pervasive, overlap between circadian functions and COVID-19 neurological symptoms, this perspective piece uses daily variations in the sense of smell and the timing of sleep and wakefulness as illustrative examples. We propose that time-stamping clinical data and testing may expand and refine diagnosis and treatment of COVID-19.

Looking for pathways related to COVID-19: confirmation of pathogenic mechanisms by SARS-CoV-2-host interactome

In the last months, many studies have clearly described several mechanisms of SARS-CoV-2 infection at cell and tissue level, but the mechanisms of interaction between host and SARS-CoV-2, determining the grade of COVID-19 severity, are still unknown. We provide a network analysis on protein–protein interactions (PPI) between viral and host proteins to better identify host biological responses, induced by both whole proteome of SARS-CoV-2 and specific viral proteins. A host-virus interactome was inferred, applying an explorative algorithm (Random Walk with Restart, RWR) triggered by 28 proteins of SARS-CoV-2. The analysis of PPI allowed to estimate the distribution of SARS-CoV-2 proteins in the host cell. Interactome built around one single viral protein allowed to define a different response, underlining as ORF8 and ORF3a modulated cardiovascular diseases and pro-inflammatory pathways, respectively. Finally, the network-based approach highlighted a possible direct action of ORF3a and NS7b to enhancing Bradykinin Storm. This network-based representation of SARS-CoV-2 infection could be a framework for pathogenic evaluation of specific clinical outcomes. We identified possible host responses induced by specific proteins of SARS-CoV-2, underlining the important role of specific viral accessory proteins in pathogenic phenotypes of severe COVID-19 patients.

Co-distribution of Light At Night (LAN) and COVID-19 incidence in the United States

Background

Light at night (LAN) as a circadian disruption factor may affect the human immune system and consequently increase an individual’s susceptibility to the severity of infectious diseases, such as COVID-19. COVID-19 infections spread differently in each state in the United States (US). The current analysis aimed to test whether there is an association between LAN and COVID-19 cases in 4 selected US states: Connecticut, New York, California, and Texas.

Methods

We analyzed clustering patterns of COVID-19 cases in ArcMap and performed a multiple linear regression model using data of LAN and COVID-19 incidence with adjustment for confounding variables including population density, percent below poverty, and racial factors.

Results

Hotspots of LAN and COVID-19 cases are located in large cities or metro-centers for all 4 states. LAN intensity is associated with cases/1 k for overall and lockdown durations in New York and Connecticut (P < 0.001), but not in Texas and California. The overall case rates are significantly associated with LAN in New York (P < 0.001) and Connecticut (P < 0.001).

Conclusions

We observed a significant positive correlation between LAN intensity and COVID-19 cases-rate/1 k, suggesting that circadian disruption of ambient light may increase the COVID-19 infection rate possibly by affecting an individual’s immune functions. Furthermore, differences in the demographic structure and lockdown policies in different states play an important role in COVID-19 infections.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11500-6.

A systems-level study reveals host-targeted repurposable drugs against SARS-CoV-2 infection

Understanding the mechanism of SARS-CoV-2 infection and identifying potential therapeutics are global imperatives. Using a quantitative systems pharmacology approach, we identified a set of repurposable and investigational drugs as potential therapeutics against COVID-19. These were deduced from the gene expression signature of SARS-CoV-2-infected A549 cells screened against Connectivity Map and prioritized by network proximity analysis with respect to disease modules in the viral-host interactome. We also identified immuno-modulating compounds aiming at suppressing hyperinflammatory responses in severe COVID-19 patients, based on the transcriptome of ACE2-overexpressing A549 cells. Experiments with Vero-E6 cells infected by SARS-CoV-2, as well as independent syncytia formation assays for probing ACE2/SARS-CoV-2 spike protein-mediated cell fusion using HEK293T and Calu-3 cells, showed that several predicted compounds had inhibitory activities. Among them, salmeterol, rottlerin, and mTOR inhibitors exhibited antiviral activities in Vero-E6 cells; imipramine, linsitinib, hexylresorcinol, ezetimibe, and brompheniramine impaired viral entry. These novel findings provide new paths for broadening the repertoire of compounds pursued as therapeutics against COVID-19.

Melatonin multifaceted pharmacological actions on melatonin receptors converging to abrogate COVID-19

Data indicate that controlling inflammatory responses to COVID-19 may be as important as antiviral therapies or could be an important adjunctive approach. Melatonin possesses anti-inflammation, antioxidation, and immune-enhancing features directly and/or indirectly through its own receptor signaling and is therefore well suited to reduce the severity of COVID-19. Studies have proposed that melatonin regulates COVID-19-associated proteins directly through regulation of molecules such as calmodulin (CALM) 1 and CALM 2, calreticulin (CalR), or myeloperoxidase (MPO) and/or indirectly through actions on GPCR (eg, MTNR1A, MTNR1B) and nuclear (eg, RORα, RORβ) melatonin receptor signaling. However, the exact mechanism(s) and doses by which melatonin reduces the severity of COVID-19 is still open for debate, warranting the need for further testing of melatonin in placebo-controlled randomized clinical trials for COVID-19.

Multimodal single-cell omics analysis identifies epithelium-immune cell interactions and immune vulnerability associated with sex differences in COVID-19

Sex differences in the susceptibility of SARS-CoV-2 infection and severity have been controversial, and the underlying mechanisms of COVID-19 in a sex-specific manner remain understudied. Here we inspected sex differences in SARS-CoV-2 infection, hospitalization, admission to the intensive care unit (ICU), sera inflammatory biomarker profiling, and single-cell RNA-sequencing (scRNA-seq) profiles across nasal, bronchoalveolar lavage fluid (BALF), and peripheral blood mononuclear cells (PBMCs) from COVID-19 patients with varying degrees of disease severities. Our propensity score-matching observations revealed that male individuals have a 29% elevated likelihood of SARS-CoV-2 positivity, with a hazard ratio (HR) 1.32 (95% confidence interval [CI] 1.18–1.48) for hospitalization and HR 1.51 (95% CI 1.24–1.84) for admission to ICU. Sera from male patients at hospital admission had elevated neutrophil–lymphocyte ratio and elevated expression of inflammatory markers (C-reactive protein and procalcitonin). We found that SARS-CoV-2 entry factors, including ACE2, TMPRSS2, FURIN, and NRP1, have elevated expression in nasal squamous cells from male individuals with moderate and severe COVID-19. We observed male-biased transcriptional activation in SARS-CoV-2-infected macrophages from BALF and sputum samples, which offers potential molecular mechanism for sex-biased susceptibility to viral infection. Cell–cell interaction network analysis reveals potential epithelium–immune cell interactions and immune vulnerability underlying male-elevated disease severity and mortality in COVID-19. Mechanistically, monocyte-elevated expression of Toll-like receptor 7 (TLR7) and Bruton tyrosine kinase (BTK) is associated with severe outcomes in males with COVID-19. In summary, these findings provide basis to decipher immune responses underlying sex differences and designing sex-specific targeted interventions and patient care for COVID-19.

Renin-Angiotensin Aldosterone System Inhibitors in Primary Prevention and COVID-19

Background

Considering the widespread risk of collider bias and confounding by indication in previous research, the associations between renin‐angiotensin aldosterone system (RAAS) inhibitor use and COVID‐19 remain unknown. Accordingly, this study tested the hypothesis that RAAS inhibitors influence the summation effect of COVID‐19 and its progression to severe outcomes.

Methods and Results

This nationwide cohort study compared all residents of Sweden, without prior cardiovascular disease, in monotherapy (as of January 1, 2020) with a RAAS inhibitor to those using a calcium channel blocker or a thiazide diuretic. Comparative cohorts were balanced using machine‐learning‐derived propensity score methods. Of 165 355 people in the analysis (51% women), 367 were hospitalized or died with COVID‐19 (246 using a RAAS inhibitor versus 121 using a calcium channel blocker or thiazide diuretic; Cox proportional hazard ratio [HR], 0.97; 95% CI, 0.74–1.27). When each outcome was assessed separately, 335 people were hospitalized with COVID‐19 (HR, 0.92; 95% CI, 0.70–1.22), and 64 died with COVID‐19 (HR, 1.22; 95% CI, 0.68–2.19). The severity of COVID‐19 outcomes did not differ between those using a RAAS inhibitor and those using a calcium channel blocker or thiazide diuretic (ordered logistic regression odds ratio, 1.01; 95% CI, 0.89–1.14).

Conclusions

Despite potential limitations, this study is among the best available evidence that RAAS inhibitor use in primary prevention does not increase the risk of severe COVID‐19 outcomes; presenting strong data from which scientists and policy makers alike can base, with greater confidence, their current position on the safety of using RAAS inhibitors during the COVID‐19 pandemic.

Pedagogy and innovative care tenets in COVID-19 pandemic: An enhancive way through Dentistry 4.0

The global oral healthcare sector has now woken to implement Dentistry 4.0. The implementation of this revolution is feasible with extensive digital and advanced technologies applications and the adoption of new sets of processes in dentistry & its support areas. COVID-19 has bought new challenges to dental professionals and patients towards their customised requirements, regular dental health checkups, fast-paced and safe procedures. People are not visiting the dentist even for mild cases as they fear COVID-19 infection. We see that this set of technologies will help improve health education and treatment process and materials and minimise the infection. During the COVID-19 pandemic, there is a need to understand the possible impact of Dentistry 4.0 for education and innovative care. This paper discusses the significant benefits of Dentistry 4.0 technologies for the smart education platform and dentistry treatment. Finally, this article identifies twenty significant enhancements in dental education and effective care platforms during the COVID-19 pandemic by employing Dentistry 4.0 technologies. Thus, proper implementation of these technologies will improve the process efficiency in healthcare during the COVID-19 pandemic. Dentistry 4.0 technologies drive innovations to improve the quality of internet-connected healthcare devices. It creates automation and exchanges data to make a smart health care system. Therefore, helps better healthcare services, planning, monitoring, teaching, learning, treatment, and innovation capability. These technologies moved to smart transportation systems in the hospital during the COVID-19 Pandemic. Modern manufacturing technologies create digital transformation in manufacturing, optimises the operational processes and enhances productivity.

The Coronavirus Disease 2019 (COVID-19): Key Emphasis on Melatonin Safety and Therapeutic Efficacy

Viral infections constitute a tectonic convulsion in the normophysiology of the hosts. The current coronavirus disease 2019 (COVID-19) pandemic is not an exception, and therefore the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, like any other invading microbe, enacts a generalized immune response once the virus contacts the body. Melatonin is a systemic dealer that does not overlook any homeostasis disturbance, which consequently brings into play its cooperative triad, antioxidant, anti-inflammatory, and immune-stimulant backbone, to stop the infective cycle of SARS-CoV-2 or any other endogenous or exogenous threat. In COVID-19, the corporal propagation of SARS-CoV-2 involves an exacerbated oxidative activity and therefore the overproduction of great amounts of reactive oxygen and nitrogen species (RONS). The endorsement of melatonin as a possible protective agent against the current pandemic is indirectly supported by its widely demonstrated beneficial role in preclinical and clinical studies of other respiratory diseases. In addition, focusing the therapeutic action on strengthening the host protection responses in critical phases of the infective cycle makes it likely that multi-tasking melatonin will provide multi-protection, maintaining its efficacy against the virus variants that are already emerging and will emerge as long as SARS-CoV-2 continues to circulate among us.

Update on Functional Inhibitors of Acid Sphingomyelinase (FIASMAs) in SARS-CoV-2 Infection

The SARS-CoV-2 outbreak is characterized by the need of the search for curative drugs for treatment. In this paper, we present an update of knowledge about the interest of the functional inhibitors of acid sphingomyelinase (FIASMAs) in SARS-CoV-2 infection. Forty-nine FIASMAs have been suggested in the treatment of SARS-CoV-2 infection using in silico, in vitro or in vivo studies. Further studies using large-sized, randomized and double-blinded controlled clinical trials are needed to evaluate FIASMAs in SARS-CoV-2 infection as off-label therapy.

The influence of selection bias on identifying an association between allergy medication use and SARS-CoV-2 infection

BACKGROUND

Medications to prevent and treat SARS-CoV-2 infection are needed to complement emerging vaccinations. Recent in vitro and electronic health record (EHR) studies suggested that certain allergy medications could prevent SARS-CoV-2 infection. We sought to carefully examine the potential selection bias associated with utilizing EHRs in these settings.

METHODS

We analyzed associations of three allergy medications (cetirizine, diphenhydramine or hydroxyzine) with testing negative for SARS-CoV-2, measuring the potential effect of selection bias on these associations. We used a retrospective cohort of EHR data from 230,376 patients (18 years+) who visited outpatient clinicians in a single, large academic center at least once but were never hospitalized (10/1/2019-6/1/2020). Main exposures included EHR documentation of three allergy medications and allergy, with an intermediate outcome of receipt of a SARS-CoV-2 test, and the primary outcome as testing negative.

FINDINGS

SARS-CoV-2 testing rates varied by sex, age, race/ethnicity and insurance. Increasing age and public insurance were associated with a higher adjusted odds of test negativity, while being Black or Hispanic was significantly associated with test positivity. Allergy diagnosis and use of any of three allergy medications were each associated with a higher likelihood of receiving a test (e.g. diphenhydramine - Odds Ratio (OR) 2.99, 95% Confidence Interval (CI) 2.73, 3.28; cetirizine 1.75 (95% CI 1.60, 1.92)). Among those tested, only use of diphenhydramine was associated with a negative SARS-CoV-2 test (adjusted OR = 2.23, 95% CI 1.10, 4.55). However, analyses revealed that selection bias may be responsible for the apparent protective effect of diphenhydramine.

INTERPRETATION

Diphenhydramine use was associated with more SARS-CoV-2 testing and subsequent higher odds for negative tests. While EHR-based observational studies can inform a need for interventional trials, this study revealed limitations of EHR data. The finding that diphenhydramine documentation conferred a higher odds of testing negative for SARS-CoV-2 must be interpreted with caution due to probable selection bias.Abbreviations: SARS-CoV-2, ACE2, COVID-19, EHR.

Using machine learning approaches for multi-omics data analysis: A review

With the development of modern high-throughput omic measurement platforms, it has become essential for biomedical studies to undertake an integrative (combined) approach to fully utilise these data to gain insights into biological systems. Data from various omics sources such as genetics, proteomics, and metabolomics can be integrated to unravel the intricate working of systems biology using machine learning-based predictive algorithms. Machine learning methods offer novel techniques to integrate and analyse the various omics data enabling the discovery of new biomarkers. These biomarkers have the potential to help in accurate disease prediction, patient stratification and delivery of precision medicine. This review paper explores different integrative machine learning methods which have been used to provide an in-depth understanding of biological systems during normal physiological functioning and in the presence of a disease. It provides insight and recommendations for interdisciplinary professionals who envisage employing machine learning skills in multi-omics studies.

Pretraining model for biological sequence data

With the development of high-throughput sequencing technology, biological sequence data reflecting life information becomes increasingly accessible. Particularly on the background of the COVID-19 pandemic, biological sequence data play an important role in detecting diseases, analyzing the mechanism and discovering specific drugs. In recent years, pretraining models that have emerged in natural language processing have attracted widespread attention in many research fields not only to decrease training cost but also to improve performance on downstream tasks. Pretraining models are used for embedding biological sequence and extracting feature from large biological sequence corpus to comprehensively understand the biological sequence data. In this survey, we provide a broad review on pretraining models for biological sequence data. Moreover, we first introduce biological sequences and corresponding datasets, including brief description and accessible link. Subsequently, we systematically summarize popular pretraining models for biological sequences based on four categories: CNN, word2vec, LSTM and Transformer. Then, we present some applications with proposed pretraining models on downstream tasks to explain the role of pretraining models. Next, we provide a novel pretraining scheme for protein sequences and a multitask benchmark for protein pretraining models. Finally, we discuss the challenges and future directions in pretraining models for biological sequences.

Network medicine links SARS-CoV-2/COVID-19 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment

BACKGROUND

Dementia-like cognitive impairment is an increasingly reported complication of SARS-CoV-2 infection. However, the underlying mechanisms responsible for this complication remain unclear. A better understanding of causative processes by which COVID-19 may lead to cognitive impairment is essential for developing preventive and therapeutic interventions.

METHODS

In this study, we conducted a network-based, multimodal omics comparison of COVID-19 and neurologic complications. We constructed the SARS-CoV-2 virus-host interactome from protein-protein interaction assay and CRISPR-Cas9-based genetic assay results and compared network-based relationships therein with those of known neurological manifestations using network proximity measures. We also investigated the transcriptomic profiles (including single-cell/nuclei RNA-sequencing) of Alzheimer's disease (AD) marker genes from patients infected with COVID-19, as well as the prevalence of SARS-CoV-2 entry factors in the brains of AD patients not infected with SARS-CoV-2.

RESULTS

We found significant network-based relationships between COVID-19 and neuroinflammation and brain microvascular injury pathways and processes which are implicated in AD. We also detected aberrant expression of AD biomarkers in the cerebrospinal fluid and blood of patients with COVID-19. While transcriptomic analyses showed relatively low expression of SARS-CoV-2 entry factors in human brain, neuroinflammatory changes were pronounced. In addition, single-nucleus transcriptomic analyses showed that expression of SARS-CoV-2 host factors (BSG and FURIN) and antiviral defense genes (LY6E, IFITM2, IFITM3, and IFNAR1) was elevated in brain endothelial cells of AD patients and healthy controls relative to neurons and other cell types, suggesting a possible role for brain microvascular injury in COVID-19-mediated cognitive impairment. Overall, individuals with the AD risk allele APOE E4/E4 displayed reduced expression of antiviral defense genes compared to APOE E3/E3 individuals.

CONCLUSION

Our results suggest significant mechanistic overlap between AD and COVID-19, centered on neuroinflammation and microvascular injury. These results help improve our understanding of COVID-19-associated neurological manifestations and provide guidance for future development of preventive or treatment interventions, although causal relationship and mechanistic pathways between COVID-19 and AD need future investigations.